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Cited by 115Ethics and Social Impacts of AIInnovation, Technology, and SocietyArtificial Intelligence Applications

Envisioning Communities: A Participatory Approach Towards AI for Social Good

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Bondi, Elizabeth, Xu, Lily, Acosta-Navas, Diana, Killian, Jackson A.·2021·Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society
DOI 10.1145/3461702.3462612
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Abstract

Research in artificial intelligence (AI) for social good presupposes some definition of social good, but potential definitions have been seldom suggested and never agreed upon. The normative question of what AI for social good research should be "for" is not thoughtfully elaborated, or is frequently addressed with a utilitarian outlook that prioritizes the needs of the majority over those who have been historically marginalized, brushing aside realities of injustice and inequity. We argue that AI for social good ought to be assessed by the communities that the AI system will impact, using as a guide the capabilities approach, a framework to measure the ability of different policies to improve human welfare equity. Furthermore, we lay out how AI research has the potential to catalyze social progress by expanding and equalizing capabilities. We show how the capabilities approach aligns with a participatory approach for the design and implementation of AI for social good research in a framework we introduce called PACT, in which community members affected should be brought in as partners and their input prioritized throughout the project. We conclude by providing an incomplete set of guiding questions for carrying out such participatory AI research in a way that elicits and respects a community's own definition of social good.

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  • Communities most in need of public services are also most at-risk of being disadvantaged by AI systems.

    “Further, in many instances, the communities most in need of public services are also the communities that are most at-risk of being disadvantaged by AI systems [15, 17, 33, 95, 100, 102].”

    From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [17]

    Section 6.1 (page unavailable) urges prioritizing vulnerable, marginalized communities, and Section 6.2 (page unavailable) reports that a biased algorithm led to Black communities being included in certain health programs less frequently. These passages support the risk of AI disadvantage in a service setting, but do not establish that communities most in need of public services are generally those most at risk. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Human-centered AI calls to actively involve people in AI design to ensure systems better reflect the values, preferences and needs of users and other impacted stakeholders.

    “The domain of Human-centered AI HCAI calls to actively involve people in AI design to ensure systems better reflect the values, preferences and needs of users, and other impacted stakeholders (e.g., [4, 8, 16, 99, 101, 104, 110]).”

    From Engaging Communities Meaningfully in Defining Disability Representation for AI Image Generation (2026) · cites this paper as [16]

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Research works printed but not linked: 54

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Authors
Bondi, E., Xu, L., Acosta-Navas, D., & Killian, J. A.
Affiliations
Harvard University (US)
ORCID
Venue
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society
Publisher
ACM
Published
2021-07-21
Pages
425-436
ISSN
3065-8365 (ISSN-L)
DOI
10.1145/3461702.3462612
OpenAlex
W3159003756
Cited by
115
References
72
Citations by year
2026: 22 · 2025: 36 · 2024: 29 · 2023: 18 · 2022: 9 · 2021: 1
FWCI
13.13
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
  • Proceedings of the AAAI/ACM Conference on AI Ethics and Society (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Sociology and Political Science › Innovation, Technology, and Society
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
AI for social good, capability approach, participatory design, community participation, social justice, marginalized communities, AI ethics

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